Literature DB >> 23888187

Protein quantitation using iTRAQ: Review on the sources of variations and analysis of nonrandom missingness.

Ruiyan Luo1, Hongyu Zhao.   

Abstract

As a technique that allows simultaneous quantitation of proteins in multiple samples, iTRAQ (isobaric Tags for Relative and Absolute Quantitation) has gained increased interest and applications in proteomics research. Despite its success, iTRAQ data present a number of statistical challenges even after the proteins and peptides are identified and the peak areas of the reported ions are estimated for peptide intensities. In this article, we review recent studies on the analysis of iTRAQ data, the computation problems involved and the nonrandom missingness in the iTRAQ data.

Entities:  

Keywords:  ANOVA; Bayesian hierarchical model; Mass spectrometry; Nonrandom missing; iTRAQ

Year:  2012        PMID: 23888187      PMCID: PMC3719432          DOI: 10.4310/sii.2012.v5.n1.a9

Source DB:  PubMed          Journal:  Stat Interface        ISSN: 1938-7989            Impact factor:   0.582


  30 in total

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